基于大数据服务平台的电动汽车有序充放电管理
|
摘要
电动汽车(electric vehicle,EV)有序充放电管理可以促进错峰用电和平抑可再生能源发电出力波动。然而,在需求侧,EV有序充放电管理还存在调度任务难执行、充放电参与不便利和信息交互不通畅等问题。在此背景下,分别针对"配电系统-EV"层面和"输电系统-配电系统"层面制定EV有序充放电管理策略。首先,针对在"配电系统-用户"层面的EV大量分散接入、难以统一优化的问题,采用虚拟电厂(virtual power plant,VPP)建模,并制定灵活的管理机制来引导EV有序充放电。为此,开发多功能大数据服务平台(multi-function big-data service platform,M DSP)来分析EV的充放电特性,并通过发布分时电价和签订EV短期充放电协议(short-term charging and discharging agreement,SCDA)等措施,减小EV充放电功率预测不确定性对配电系统调度和运行的影响。接着,基于在"配电系统-EV"层面预测的EV充放电功率,建立"输电系统-配电系统"层面的双层分阶段机会约束规划模型;该模型分别以输电系统调度机构和VPP为上层和下层模型的优化主体,并包括日前优化和实时优化2个阶段。最后,对IEEE 30节点电力系统进行扩展,形成包括输电和配电网络的87节点算例系统,并用该系统对所提出的方法进行说明。
The coordinated charging and discharging management of electric vehicles( EVs) plays a significant role in improving load profiles and mitigating power fluctuation from renewable energy power generation. However,there are still some problems to be solved in the demand side,such as difficulty in enforcing dispatching tasks,inconvenience in charging and discharging,occasional interruptions of information interactions. Given this background,coordinated charging and discharging strategies are proposed separately for the two levels,i. e.,"the power distribution system( PDS) to EVs"and"the power transmission system( PTS) to PDS". Firstly,a flexible management mechanism for "PDS to EVs"level is proposed considering numerous decentralized EVs and hence heavy computational burden. To this end,a multi-function big data service platform( MDSP) is developed for analyzing the performance of charging and discharging of EVs,with respect to time-of-use( TOU) pricing and short-term charging and discharging agreement( SCDA). On the basis of the predicted EV charging and discharging power from the "PDS to EVs"level,a bi-layer two-stage chance-constrained programming model is then proposed for the "PTS to PDS "level,in which the optimal subjects of upper layer and down layer are the independent system operator( ISO) in the transmission system and VPPs,separately,including day-ahead and real-time dispatching. Finally,a sample power system with 87 buses,including both PTS and PDS,is attained by expanding the IEEE30-bus power system,and then served to demonstrate the features of the proposed method.
The coordinated charging and discharging management of electric vehicles( EVs) plays a significant role in improving load profiles and mitigating power fluctuation from renewable energy power generation. However,there are still some problems to be solved in the demand side,such as difficulty in enforcing dispatching tasks,inconvenience in charging and discharging,occasional interruptions of information interactions. Given this background,coordinated charging and discharging strategies are proposed separately for the two levels,i. e.,"the power distribution system( PDS) to EVs"and"the power transmission system( PTS) to PDS". Firstly,a flexible management mechanism for "PDS to EVs"level is proposed considering numerous decentralized EVs and hence heavy computational burden. To this end,a multi-function big data service platform( MDSP) is developed for analyzing the performance of charging and discharging of EVs,with respect to time-of-use( TOU) pricing and short-term charging and discharging agreement( SCDA). On the basis of the predicted EV charging and discharging power from the "PDS to EVs"level,a bi-layer two-stage chance-constrained programming model is then proposed for the "PTS to PDS "level,in which the optimal subjects of upper layer and down layer are the independent system operator( ISO) in the transmission system and VPPs,separately,including day-ahead and real-time dispatching. Finally,a sample power system with 87 buses,including both PTS and PDS,is attained by expanding the IEEE30-bus power system,and then served to demonstrate the features of the proposed method.
引文
[1]赵俊华,文福拴,薛禹胜,等.电力信息物理融合系统的建模分析与控制研究框架[J].电力系统自动化,2011,35(16):1-8.ZHAO Junhua,WEN Fushuan,XUE Yusheng,et al.Modeling analysis and control research framework of cyber physical powersystems[J].Automation of Electric Power Systems,2011,35(16):1-8.
[2]陈思,张焰,薛贵挺,等.考虑与电动汽车换电站互动的微电网经济调度[J].电力自动化设备,2015,35(4):60-69.CHEN Si,ZHANG Yan,XUE Guiting,et al.Microgrid economic dispatch considering interaction with EV BSS[J].Electric Power Automation Equipment,2015,35(4):60-69.
[3]VERZIJLBERGH R A,GROND MO W,LUKSZO Z,et al.Network impacts and cost savings of controlled EV charging[J].IEEE Transactions on Smart Grid,2012,3(3):1203-1212.
[4]许少伦,严正,冯冬涵,等.基于多智能体的电动汽车充电协同控制策略[J].电力自动化设备,2014,34(11):7-13.XU Shaolun,YAN Zheng,FENG Donghan,et al.Cooperative charging control strategy of electric vehicles based on multi-agent[J].Electric Power Automation Equipment,2014,34(11):7-13.
[5]SORTOMME E,HINDI MM,MACPHERSON S D J,et al.Coordinated charging of plug-in hybrid electric vehicles to minimize distribution system losses[J].IEEE Transactions on Smart Grid,2011,2(1):198-205.
[6]邹文,吴福保,刘志宏.实时电价下插电式混合动力汽车智能集中充电策略[J].电力系统自动化,2011,35(14):62-67.ZOU Wen,WU Fubao,LIU Zhihong.Centralized charging strategies of plug-in hybrid electric vehicles under electricity markets based on spot pricing[J].Automation of Electric Power Systems,2011,35(14):62-67.
[7]徐智威,胡泽春,宋永华,等.基于动态分时电价的电动汽车充电站有序充电策略[J].中国电机工程学报,2014,34(22):3638-3646.XU Zhiwei,HU Zechun,SONG Yonghua,et al.Coordinated charging strategy for PEV charging stations based on dynamic timeof-use tariffs[J].Proceedings of the CSEE,2014,34(22):3638-3646.
[8]MOON S K,KIMJ O.Balanced charging strategies for electric vehicles on power systems[J].Applied Energy,2017,189(3):44-54.
[9]姚伟锋,赵俊华,文福拴,等.基于双层优化的电动汽车充放电调度策略[J].电力系统自动化,2012,36(11):30-37.YAO Weifeng,ZHAO Junhua,WEN Fushuan,et al.A charging and discharging strategy for electric vehicles based on bi-level optimization[J].Automation of Electric Power Systems,2012,36(11):30-37.
[10]MA Z,CALLAWAY D,HISKENS I.Decentralized charging control for large populations of plug-in electric vehicles[J].IEEE Transactions on Control Systems Technology,2013,21(1):67-78.
[11]刘东奇,王耀南,申永鹏.基于T-S模糊控制器的电动汽车V2G智能充电站控制策略[J].电工技术学报,2016,31(2):206-214.LIU Dongqi,WANG Yaonan,SHEN Yongpeng.Research of V2G smart charging station control strategy using T-S fuzzy controller[J].Transactions of China Electrotechnical Society,2016,31(2):206-214.
[12]杨洪明,李明,文福拴,等.利用实时交通信息感知的电动汽车路径选择和充电导航策略[J].电力系统自动化,2017,41(11):106-113.YANG Hongming,LI Ming,WEN Fushuan,et al.Route selection and charging navigation strategy for electric vehicles employing realtime traffic information perception[J].Automation of Electric Power Systems,2017,41(11):106-113.
[13]姚伟锋,赵俊华,文福拴,等.配电系统与电动汽车充电网络的协调规划[J].电力系统自动化,2015,39(9):10-18.YAO Weifeng,ZHAO Junhua,WEN Fushuan,et al.Coordinated planning for power distribution system and electric vehicle charging infrastructures[J].Automation of Electric Power Systems,2015,39(9):10-18.
[14]BAE S,KWASINSKI A.Spatial and temporal model of electric vehicle charging demand[J].IEEE Transactions on Smart Grid,2012,3(1):394-403.
[15]LI Z,GUO Q,SUN H,et al.ADMM-based decentralized demand response method in electric vehicle virtual power plant[C]//IEEE Power and Energy Society General Meeting.Boston,USA:IEEE,2016:1-5.
[16]刘祚宇,齐峰,文福拴,等.含电动汽车虚拟电厂参与碳交易时的经济与环境调度[J].电力建设,2017,38(9):45-52.LIU Zuoyu,QI Feng,WEN Fushuan,et al.Economic and environmental dispatching in electric vehicles embedded virtual power plants with participation in carbon trading[J].Electric Power Construction,2017,38(9):45-52.
[17]陈炜.含电动汽车储能与分布式风力发电的虚拟发电厂优化运行[J].电力自动化设备,2016,36(10):45-50.CHEN Wei.Optimal operation of virtual power plant with electric vehicles and distributed wind farms[J].Electric Power Automation Equipment,2016,36(10):45-50.
[18]HASSANA S,MARMARAS C E,XYDAS E S,et al.Integration of wind power using V2G as aexible storage[C]//IET Conference on Power in Unity:a Whole System Approach.London,United Kingdom:IET,2013:1-5.
[19]YAO W,CHUNG C Y,WEN F,et al.Scenario-based comprehensive expansion planning for distribution systems considering integration of plug-in electric vehicles[J].IEEE Transactions on Power Systems,2015,31(1):317-328.
[20]王小蕾,姚伟锋,文福拴,等.电动汽车有序充电管理的综合效益分析[J].电力建设,2015,36(7):194-201.WANG Xiaolei,YAO Weifeng,WEN Fushuan,et al.Comprehensive benefit analysis of coordinated charging management of electric vehicles[J].Electric Power Construction,2015,36(7):194-201.
[21]张洪财,胡泽春,宋永华,等.考虑时空分布的电动汽车充电负荷预测方法[J].电力系统自动化,2014,38(1):13-20.ZHANG Hongcai,HU Zechun,SONG Yonghua,et al.A prediction method for electric vehicle charging load considering spatial and temporal distribution[J].Automation of Electric Power Systems,2014,38(1):13-20.
[22]ZANG X,FELIPE P.VISTA IV,KIL TO CHONG.Fast global kernel fuzzy c-means clustering algorithm for consonant/vowel segmentation of speech signal[J].Journal of Zhejiang UniversityScience C(Computers&Electronics),2014,15(7):551-563.
[23]ONGSAKUL W,PETCHARAKS N.Unit commitment by enhanced adaptive Lagrangian relaxation[J].IEEE Transactions on Power Systems,2004,19(1):620-628.
[24]HIEU Trung Nguyen,LONG Bao Le.Bidding strategy for virtual power plant with intraday demand response exchange market using stochastic programming[C]//IEEE International Conference on Sustainable Energy Technologies.Hanoi,Vietnam:IEEE,2016:96-101.
[25]谢应昭,卢继平.含风储混合系统的多目标机组组合优化模型及求解[J].电力自动化设备,2015,35(3):18-26.XIE Yingzhao,LU Jiping.Multi-objective unit commitment optimization model including hybrid wind-storage system and its solution[J].Electric Power Automation Equipment,2015,35(3):18-26.
[26]郑宇,赵俊华,孟科,等.计及碳交易机制的电力系统随机优化调度[J].电力建设,2017,38(6):21-27.ZHENG Yu,ZHAO Junhua,MENG Ke,et al.Carbon trading based stochastic optimal dispatching of power system[J].Electric Power Construction,2017,38(6):21-27.
[27]杨楠,刘涤尘,董开松,等.考虑柔性负荷补偿/激励机制的风电供需侧一体化随机调度方法[J].电力自动化设备,2015,35(2):15-20.YANG Nan,LIU Dichen,DONG Kaisong,et al.Integrated random scheduling for supply and demand sides of wind power system considering flexible load compensation/incentives[J].Electric Power Automation Equipment,2015,35(2):15-20.
[28]YEH H G,GAYME D F,LOW S H.Adaptive VAR control for distribution circuits with photovoltaic generators[J].IEEE Transactions on Power Systems,2012,27(3):1656-1663.
[29]YANG F,KWAN C M,CHANG C S.Multiobjective evolutionary optimization of substation maintenance using decision-varying Markov model[J].IEEE Transactions on Power Systems,2008,23(3):1328-1335.
[30]何明杰,彭春华,曹文辉,等.考虑电动汽车规模化入网的动态经济调度[J].电力自动化设备,2013,33(9):82-88.HE Mingjie,PENG Chunhua,CAO Wenhui,et al.Dynamic economic dispatch considering large-scale integration of electric vehicles[J].Electric Power Automation Equipment,2013,33(9):82-88.
[31]易琛,任建文,戚建文.考虑需求响应的风电消纳模糊优化调度研究[J].电力建设,2017,38(4):127-134.YI Chen,REN Jianwen,QI Jianwen.Fuzzy optimal dispatch of wind power consumption considering demand response[J].Electric Power Construction,2017,38(4):127-134.
[32]熊虎,向铁元,陈红坤,等.含大规模间歇式电源的模糊机会约束机组组合研究[J].中国电机工程学报,2013,33(13):36-44.XIONG Hu,XIANG Tieyuan,CHEN Hongkun,et al.Research of fuzzy chance constrained unit commitment containing[J].Proceedings of the CSEE,2013,33(13):36-44.
[33]刘凯辉.比亚迪E6纯电动汽车全生命周期评价[D].福州:福建农林大学,2016.LIU Kaihui.Life cycle assessment of BYD E6 electric vehicle[D].Fuzhou:Fujian Agriculture and Forestry University,2016.
[2]陈思,张焰,薛贵挺,等.考虑与电动汽车换电站互动的微电网经济调度[J].电力自动化设备,2015,35(4):60-69.CHEN Si,ZHANG Yan,XUE Guiting,et al.Microgrid economic dispatch considering interaction with EV BSS[J].Electric Power Automation Equipment,2015,35(4):60-69.
[3]VERZIJLBERGH R A,GROND MO W,LUKSZO Z,et al.Network impacts and cost savings of controlled EV charging[J].IEEE Transactions on Smart Grid,2012,3(3):1203-1212.
[4]许少伦,严正,冯冬涵,等.基于多智能体的电动汽车充电协同控制策略[J].电力自动化设备,2014,34(11):7-13.XU Shaolun,YAN Zheng,FENG Donghan,et al.Cooperative charging control strategy of electric vehicles based on multi-agent[J].Electric Power Automation Equipment,2014,34(11):7-13.
[5]SORTOMME E,HINDI MM,MACPHERSON S D J,et al.Coordinated charging of plug-in hybrid electric vehicles to minimize distribution system losses[J].IEEE Transactions on Smart Grid,2011,2(1):198-205.
[6]邹文,吴福保,刘志宏.实时电价下插电式混合动力汽车智能集中充电策略[J].电力系统自动化,2011,35(14):62-67.ZOU Wen,WU Fubao,LIU Zhihong.Centralized charging strategies of plug-in hybrid electric vehicles under electricity markets based on spot pricing[J].Automation of Electric Power Systems,2011,35(14):62-67.
[7]徐智威,胡泽春,宋永华,等.基于动态分时电价的电动汽车充电站有序充电策略[J].中国电机工程学报,2014,34(22):3638-3646.XU Zhiwei,HU Zechun,SONG Yonghua,et al.Coordinated charging strategy for PEV charging stations based on dynamic timeof-use tariffs[J].Proceedings of the CSEE,2014,34(22):3638-3646.
[8]MOON S K,KIMJ O.Balanced charging strategies for electric vehicles on power systems[J].Applied Energy,2017,189(3):44-54.
[9]姚伟锋,赵俊华,文福拴,等.基于双层优化的电动汽车充放电调度策略[J].电力系统自动化,2012,36(11):30-37.YAO Weifeng,ZHAO Junhua,WEN Fushuan,et al.A charging and discharging strategy for electric vehicles based on bi-level optimization[J].Automation of Electric Power Systems,2012,36(11):30-37.
[10]MA Z,CALLAWAY D,HISKENS I.Decentralized charging control for large populations of plug-in electric vehicles[J].IEEE Transactions on Control Systems Technology,2013,21(1):67-78.
[11]刘东奇,王耀南,申永鹏.基于T-S模糊控制器的电动汽车V2G智能充电站控制策略[J].电工技术学报,2016,31(2):206-214.LIU Dongqi,WANG Yaonan,SHEN Yongpeng.Research of V2G smart charging station control strategy using T-S fuzzy controller[J].Transactions of China Electrotechnical Society,2016,31(2):206-214.
[12]杨洪明,李明,文福拴,等.利用实时交通信息感知的电动汽车路径选择和充电导航策略[J].电力系统自动化,2017,41(11):106-113.YANG Hongming,LI Ming,WEN Fushuan,et al.Route selection and charging navigation strategy for electric vehicles employing realtime traffic information perception[J].Automation of Electric Power Systems,2017,41(11):106-113.
[13]姚伟锋,赵俊华,文福拴,等.配电系统与电动汽车充电网络的协调规划[J].电力系统自动化,2015,39(9):10-18.YAO Weifeng,ZHAO Junhua,WEN Fushuan,et al.Coordinated planning for power distribution system and electric vehicle charging infrastructures[J].Automation of Electric Power Systems,2015,39(9):10-18.
[14]BAE S,KWASINSKI A.Spatial and temporal model of electric vehicle charging demand[J].IEEE Transactions on Smart Grid,2012,3(1):394-403.
[15]LI Z,GUO Q,SUN H,et al.ADMM-based decentralized demand response method in electric vehicle virtual power plant[C]//IEEE Power and Energy Society General Meeting.Boston,USA:IEEE,2016:1-5.
[16]刘祚宇,齐峰,文福拴,等.含电动汽车虚拟电厂参与碳交易时的经济与环境调度[J].电力建设,2017,38(9):45-52.LIU Zuoyu,QI Feng,WEN Fushuan,et al.Economic and environmental dispatching in electric vehicles embedded virtual power plants with participation in carbon trading[J].Electric Power Construction,2017,38(9):45-52.
[17]陈炜.含电动汽车储能与分布式风力发电的虚拟发电厂优化运行[J].电力自动化设备,2016,36(10):45-50.CHEN Wei.Optimal operation of virtual power plant with electric vehicles and distributed wind farms[J].Electric Power Automation Equipment,2016,36(10):45-50.
[18]HASSANA S,MARMARAS C E,XYDAS E S,et al.Integration of wind power using V2G as aexible storage[C]//IET Conference on Power in Unity:a Whole System Approach.London,United Kingdom:IET,2013:1-5.
[19]YAO W,CHUNG C Y,WEN F,et al.Scenario-based comprehensive expansion planning for distribution systems considering integration of plug-in electric vehicles[J].IEEE Transactions on Power Systems,2015,31(1):317-328.
[20]王小蕾,姚伟锋,文福拴,等.电动汽车有序充电管理的综合效益分析[J].电力建设,2015,36(7):194-201.WANG Xiaolei,YAO Weifeng,WEN Fushuan,et al.Comprehensive benefit analysis of coordinated charging management of electric vehicles[J].Electric Power Construction,2015,36(7):194-201.
[21]张洪财,胡泽春,宋永华,等.考虑时空分布的电动汽车充电负荷预测方法[J].电力系统自动化,2014,38(1):13-20.ZHANG Hongcai,HU Zechun,SONG Yonghua,et al.A prediction method for electric vehicle charging load considering spatial and temporal distribution[J].Automation of Electric Power Systems,2014,38(1):13-20.
[22]ZANG X,FELIPE P.VISTA IV,KIL TO CHONG.Fast global kernel fuzzy c-means clustering algorithm for consonant/vowel segmentation of speech signal[J].Journal of Zhejiang UniversityScience C(Computers&Electronics),2014,15(7):551-563.
[23]ONGSAKUL W,PETCHARAKS N.Unit commitment by enhanced adaptive Lagrangian relaxation[J].IEEE Transactions on Power Systems,2004,19(1):620-628.
[24]HIEU Trung Nguyen,LONG Bao Le.Bidding strategy for virtual power plant with intraday demand response exchange market using stochastic programming[C]//IEEE International Conference on Sustainable Energy Technologies.Hanoi,Vietnam:IEEE,2016:96-101.
[25]谢应昭,卢继平.含风储混合系统的多目标机组组合优化模型及求解[J].电力自动化设备,2015,35(3):18-26.XIE Yingzhao,LU Jiping.Multi-objective unit commitment optimization model including hybrid wind-storage system and its solution[J].Electric Power Automation Equipment,2015,35(3):18-26.
[26]郑宇,赵俊华,孟科,等.计及碳交易机制的电力系统随机优化调度[J].电力建设,2017,38(6):21-27.ZHENG Yu,ZHAO Junhua,MENG Ke,et al.Carbon trading based stochastic optimal dispatching of power system[J].Electric Power Construction,2017,38(6):21-27.
[27]杨楠,刘涤尘,董开松,等.考虑柔性负荷补偿/激励机制的风电供需侧一体化随机调度方法[J].电力自动化设备,2015,35(2):15-20.YANG Nan,LIU Dichen,DONG Kaisong,et al.Integrated random scheduling for supply and demand sides of wind power system considering flexible load compensation/incentives[J].Electric Power Automation Equipment,2015,35(2):15-20.
[28]YEH H G,GAYME D F,LOW S H.Adaptive VAR control for distribution circuits with photovoltaic generators[J].IEEE Transactions on Power Systems,2012,27(3):1656-1663.
[29]YANG F,KWAN C M,CHANG C S.Multiobjective evolutionary optimization of substation maintenance using decision-varying Markov model[J].IEEE Transactions on Power Systems,2008,23(3):1328-1335.
[30]何明杰,彭春华,曹文辉,等.考虑电动汽车规模化入网的动态经济调度[J].电力自动化设备,2013,33(9):82-88.HE Mingjie,PENG Chunhua,CAO Wenhui,et al.Dynamic economic dispatch considering large-scale integration of electric vehicles[J].Electric Power Automation Equipment,2013,33(9):82-88.
[31]易琛,任建文,戚建文.考虑需求响应的风电消纳模糊优化调度研究[J].电力建设,2017,38(4):127-134.YI Chen,REN Jianwen,QI Jianwen.Fuzzy optimal dispatch of wind power consumption considering demand response[J].Electric Power Construction,2017,38(4):127-134.
[32]熊虎,向铁元,陈红坤,等.含大规模间歇式电源的模糊机会约束机组组合研究[J].中国电机工程学报,2013,33(13):36-44.XIONG Hu,XIANG Tieyuan,CHEN Hongkun,et al.Research of fuzzy chance constrained unit commitment containing[J].Proceedings of the CSEE,2013,33(13):36-44.
[33]刘凯辉.比亚迪E6纯电动汽车全生命周期评价[D].福州:福建农林大学,2016.LIU Kaihui.Life cycle assessment of BYD E6 electric vehicle[D].Fuzhou:Fujian Agriculture and Forestry University,2016.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |